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Conventional methods for positioning electroencephalography electrodes according to the international 10/20 system are based on the manual identification of the principal 10/20 landmarks via visual inspection and palpation, inducing intersession variations in their determined locations due to structural ambiguity or poor visibility. To address the variation issue, we propose an image guidance system for precision electrode placement. Following the electrode placement according to the 10/20 system, affixed electrodes are laser-scanned together with the facial surface. For subsequent procedures, the laser scan is conducted likewise after positioning the electrodes in an arbitrary manner, and following the measurement of fiducial electrode locations, frame matching is performed to determine a transformation from the coordinate frame of the position tracker to that of the laser-scanned image. Finally, by registering the intra-procedural scan of the facial surface to the reference scan, the current tracking data of the electrodes can be visualized relative to the reference goal positions without manually measuring the four principal landmarks for each trial. The experimental results confirmed that use of the electrode navigation system significantly improved the electrode placement precision compared to the conventional 10/20 system (p < 0.005). The proposed system showed the possibility of precise image-guided electrode placement as an alternative to the conventional manual 10/20 system.

BackgroundIn longitudinal electroencephalography (EEG) studies, repeatable electrode positioning is essential for reliable EEG assessment. Conventional methods use anatomical landmarks as fiducial locations for the electrode placement. Since the landmarks are manually identified, the EEG assessment is inevitably unreliable because of individual variations among the subjects and the examiners. To overcome this unreliability, an augmented reality (AR) visualization-based electrode guidance system was proposed.MethodsThe proposed electrode guidance system is based on AR visualization to replace the manual electrode positioning. After scanning and registration of the facial surface of a subject by an RGB-D camera, the AR of the initial electrode positions as reference positions is overlapped with the current electrode positions in real time. Thus, it can guide the position of the subsequently placed electrodes with high repeatability.ResultsThe experimental results with the phantom show that the repeatability of the electrode positioning was improved compared to that of the conventional 10–20 positioning system.ConclusionThe proposed AR guidance system improves the electrode positioning performance with a cost-effective system, which uses only RGB-D camera. This system can be used as an alternative to the international 10–20 system.

We validated that intrinsic parameters that describe the source position were dependent on depth for a three-dimensional object and showed that displacement can be reduced and become independent of depth by using the proposed planar source model.

Epiduroscopic laser neural decompression is an emerging therapeutic modality to treat lumbar spine pathologies including chronic low back pain, spinal stenosis, and disk herniation via catheter insertion followed by laser ablation of the lesion. Despite the efficacy of epiduroscopic laser neural decompression, excessive radiation doses due to fluoroscopy during epiduroscopic laser neural decompression have limited its widespread application. To address the issue, we propose a surgical navigation system to assist in epiduroscopic laser neural decompression procedures using radiation-free image guidance. An electromagnetic tracking system was used as the basic modality to track the internal location of the surgical instrument with respect to the patient body. Patient-to-image registration was carried out using the point-based registration method to determine the transformation between the coordinate system of the patient and that of the medical images. We applied the proposed system in epiduroscopic laser neural decompression procedures to assess its effectiveness, and the outcomes confirmed its clinical feasibility. To the best of our knowledge, this is a report on the first surgical navigation applied for epiduroscopic laser neural decompression procedure.

We proposed and demonstrated the effectiveness of a hybrid method that uses both artificial and anatomical landmarks for patient-to-image registration. The experimental results confirmed that an improvement in TRE was evident by the proposed method, suggesting its feasibility in various spinal surgeries.

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